source("./commons/setupNotebook.R")
# Factor the dataframes to get cleaner setup of column dimensions
df.submissions <- df.submissions %>% factor.data.frame()
#save.plot.png <- TRUE
save.plot.png <- FALSE
plot_output_dir <- "output/plots/00_Energy"
if (!dir.exists("output/plots/00_Energy")) {
dir.create("output/plots/00_Energy")
}
if(FALSE) { # list available variables, similar to submission_overview
reportedVariables <- df.submissions %>%
select(model, variable, unit) %>%
unique() %>%
mutate(exists = 1) %>% # Create a column for presence
pivot_wider(names_from = model, values_from = exists, values_fill = 0)
View(reportedVariables)
# write.csv(reportedVariables,"reportedVariables.csv", row.names = FALSE)
}
selectedLowScens <- c(
"SSP2 - Low Emissions",
"SSP2 - Very Low after High Overshoot",
"SSP2 - Very Low with Limited Overshoot",
"SSP1 - Very Low with Limited Overshoot",
NULL
)
selectedLowScens <- factor(selectedLowScens, levels = selectedLowScens)
scen.linePlots <- selectedLowScens
scenarios.energyAreaPlots <- selectedLowScens
scen.energyBarPlots <- filterScenarios
period.linePlots <- c(seq(2020, 2050, 5))
period.energyAreaPlots <- seq(2020, 2100, 5)
year.energyBarPlots <- 2060
Lineplots
lp_vars <- c(
"Primary Energy|Gas",
"Primary Energy|Coal",
"Primary Energy|Oil",
"Secondary Energy|Electricity|Gas",
"Secondary Energy|Electricity|Oil",
"Secondary Energy|Electricity|Coal",
"Electrification", # computed in setupNotebook.R
NULL
)
for (v in lp_vars) {
p <- plotLinesOneScenario(
plot.var = v,
plot.scen = scen.linePlots,
plot.region = "World",
plot.period = period.linePlots,
submissions = df.submissions,
historical = df.historical,
model.colors = plot.model.colors
)
p <- p + guides(color = guide_legend(nrow = 3))
print(p)
#if (save.plot.png) {
# ggsave(paste0(plot_output_dir, "/lineplot_", gsub("[^a-zA-Z0-9]", "", v), ".png"), p)
#}
}
Lineplots with AR6 Data
lp_vars <- c(
"Emissions|CO2",
"Primary Energy|Gas"
)
for(v in lp_vars) {
p <- plotLinesOneScenario(
plot.var = v,
plot.scen = scen.linePlots,
plot.region = "World",
submissions = df.submissions,
historical = filter(df.ar6, model %in% IMPs.AR6$identifier),
model.colors = plot.model.colors
)
print(p)
}
Marked Lineplots with combined models
# To change the figure size depending on the number of facets, adapt the header of this chunk.
mlp_vars <- c(
"Secondary Energy|Electricity|Solar",
"Secondary Energy|Electricity|Wind",
"Secondary Energy|Electricity|Nuclear",
"Secondary Energy|Electricity|Hydro",
"CCS Estimate",
NULL
)
df.plot_CCS <- df.submissions %>%
calc_addVariable("`CCS Estimate`" = "(`Primary Energy|Biomass|w/ CCS` * 0.1 + `Primary Energy|Coal|w/ CCS` * 0.1 + `Primary Energy|Gas|w/ CCS`* 0.06) * 0.9 ", units = "GtCO2/yr", only.new = F) %>%
filter(variable %in% mlp_vars)
plot.hist <- df.historical %>% filter(variable %in% mlp_vars, model == "Ember")
for (v in mlp_vars) {
plotMarkedLinesNearTerm2(
plot.var = v,
historical = plot.hist,
plot.period = period.linePlots,
plot.scen = c(SSP3, SSP5, SSP2, SSP1),
plot.region = "World",
line.colors = plot.model.colors,
line.types = plot.SSP.linetype,
submissions = df.plot_CCS,
separate.models = FALSE
) %>% print()
}
Marked Lineplots with separate models
# To change the figure size depending on the number of facets, adapt the header of this chunk.
mlp_vars <- c(
"Emissions|CO2|Energy and Industrial Processes" ,
"Emissions|CO2",
"Emissions|CO2|AFOLU",
"Price|Carbon",
"Final Energy",
"Final Energy|Electricity",
"Primary Energy|Coal",
"Primary Energy|Gas",
"Primary Energy|Oil",
"CCS Estimate",
NULL
)
df.historical <-df.historical %>% factor.data.frame()
for (v in mlp_vars) {
plotMarkedLinesNearTerm(
plot.var = v,
plot.scen = c(SSP1, SSP2, SSP3, SSP5),
plot.region = "World",
plot.period = period.linePlots,
submissions = df.plot_CCS,
line.colors = brewer.pal(6, "Dark2"),
line.types = plot.SSP.linetype,
historical = df.historical %>% filter(model != "BP"),
separate.models = TRUE
) %>% print()
}
## NULL
## NULL
## NULL
## NULL
## NULL
## NULL
## NULL
## NULL
## NULL
Regional carbon prices per model
mlp_vars <- c(
"Price|Carbon",
NULL
)
mlp.emi.scens <- c(
"Low Emissions",
"Very Low with Limited Overshoot",
NULL
)
for (v in mlp.emi.scens) {
print(paste("Carbon price in", v, "scenarios"))
plotMarkedLinesRegional(
plot.var = "Price|Carbon",
plot.scen = v,
plot.region = c(RegionsTen, "World"),
plot.period = period.linePlots,
submissions = df.submissions,
line.colors = c(brewer.pal(11, "Paired"), "#000000"),
line.types = plot.SSP.linetype,
historical = df.historical,
separate.models = TRUE
) %>% print()
}
## [1] "Carbon price in Low Emissions scenarios"
## [1] "Carbon price in Very Low with Limited Overshoot scenarios"
Primary Energy
total <- "Primary Energy"
pe_data <- tribble(
~variable, ~label, ~color,
"Primary Energy|Other", "Other", "grey",
"Primary Energy|Solar", "Solar", "#ffcc00",
"Primary Energy|Wind", "Wind", "#337fff",
"Primary Energy|Geothermal", "Geothermal", "#e51900",
"Primary Energy|Hydro", "Hydro", "#191999",
"Primary Energy|Ocean", "Ocean", "blue",
"Primary Energy|Nuclear", "Nuclear", "#ff33ff",
"Primary Energy|Biomass|w/ CCS", "Bio-CCS", colorspace::lighten("#338833", 0.5),
"Primary Energy|Biomass|w/o CCS", "Biomass", "#338833",
"Primary Energy|Gas|w/ CCS", "Gas-CCS", colorspace::lighten("#999959", 0.5),
"Primary Energy|Gas|w/o CCS", "Gas", "#999959",
"Primary Energy|Oil", "Oil", "#663a00",
"Primary Energy|Coal|w/ CCS", "Coal-CCS", colorspace::lighten("#0c0c0c", 0.5),
"Primary Energy|Coal|w/o CCS", "Coal", "#0c0c0c"
)
# "Primary Energy|Biomass" = "Biomass",
# "Primary Energy|Gas" = "Gas",
# "Primary Energy|Coal" = "Coal",
pe.colors <- setNames(pe_data$color, pe_data$label)
pe.labels <- setNames(pe_data$label, pe_data$variable)
pe.vars <- names(pe.labels)
plotArea(
submissions = df.submissions,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = pe.vars,
plot.var.labels = pe.labels,
plot.colors = pe.colors,
y_label = "Primary Energy\n(EJ/yr)",
total = total,
interpolate = T,
total.size = 1.1
)
plotStackedBarModScen(
submissions = df.submissions,
plot.scen = scen.energyBarPlots,
plot.region = "World",
plot.vars = pe.vars,
plot.var.labels = pe.labels,
plot.colors = pe.colors,
plot.period = c(year.energyBarPlots),
y_label = paste0(total, " in ", year.energyBarPlots, "\n(EJ/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
)
Electricity production
total <- "Secondary Energy|Electricity"
se_data <- tribble(
~variable, ~label, ~color,
"Other", "Other", "#ccc",
"Hydrogen", "Hydrogen", "#aff",
"Solar", "Solar", "#fc0",
"Waste", "Waste", "#2aa",
"Wind|Offshore", "Wind offsh", "#24f",
"Wind|Onshore", "Wind onsh", "#48f",
"Ocean", "Ocean", "#006",
"Geothermal", "Geothermal", "#e20",
"Hydro", "Hydro", "#229",
"Nuclear", "Nuclear", "#f3f",
"Biomass", "Biomass", "#060",
"Gas", "Gas", "#774",
"Oil", "Oil", "#630",
"Coal", "Coal", "#111"
)
#"Trade|Secondary Energy|Electricity|Volume" = "Import",
se.colors <- setNames(se_data$color, se_data$label)
se.labels <- setNames(se_data$label, se_data$variable)
names(se.labels) <- paste0("Secondary Energy|Electricity|", names(se.labels))
se.vars <- names(se.labels)
plotArea(
submissions = df.submissions,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = se.vars,
plot.var.labels = se.labels,
plot.colors = se.colors,
y_label = "Electricity\n(EJ/yr)",
total = total,
interpolate = T,
total.size = 1.1
)
## The following `from` values were not present in `x`: Secondary Energy|Electricity|Waste, Secondary Energy|Electricity|Ocean
plotStackedBarModScen(
submissions = df.submissions,
plot.scen = scen.energyBarPlots,
plot.region = "World",
plot.vars = se.vars,
plot.var.labels = se.labels,
plot.colors = se.colors,
plot.period = c(year.energyBarPlots),
y_label = paste0(total, " in ", year.energyBarPlots, "\n(EJ/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
)
## The following `from` values were not present in `x`: Secondary Energy|Electricity|Waste, Secondary Energy|Electricity|Ocean
### Battery-electric vehicles
vehicle_data <- tribble(
~variable, ~label, ~color,
"Fuel-Cell-Electric", "Fuel-cell", "#aaffff",
"Battery-Electric", "Battery", "#ffcc00",
"Plug-in Hybrid", "Hybrid", "#ee22ee",
"Internal Combustion", "Combustion", "#663a00",
)
for(metric in c("Sales", "Stocks")) {
data_LDV <- vehicle_data %>% mutate(
variable = paste0(metric, "|Transportation|Light-Duty Vehicle|",variable),
label = paste("LDV", label))
data_truck <- vehicle_data %>% mutate(
variable = paste0(metric, "|Transportation|Truck|",variable),
label = paste("Truck", label),
color = colorspace::darken(color, 0.2))
data_both <- bind_rows(data_truck, data_LDV)
unit <- unique(filter(df.submissions, variable %in% data_both$variable)$unit)
vehicle.colors <- setNames(data_both$color, data_both$label)
vehicle.labels <- setNames(data_both$label, data_both$variable)
plotArea(
submissions = df.submissions,
plot.scen = defScens,
plot.period = period.energyAreaPlots,
plot.vars = data_both$variable,
plot.var.labels = vehicle.labels,
plot.colors = vehicle.colors,
y_label = paste0(metric, " (", unit, ")"),
#total = "Primary Energy",
interpolate = T,
total.size = 1.1
) %>% print()
}
## The following `from` values were not present in `x`: Sales|Transportation|Truck|Plug-in Hybrid
## Warning: Removed 1875 rows containing non-finite outside the scale range (`stat_align()`).
## The following `from` values were not present in `x`: Stocks|Transportation|Truck|Plug-in Hybrid
Final Energy
FE carriers
vars <- c(
"Final Energy",
"Final Energy|Industry",
# "Final Energy|Non-Energy Use",
"Final Energy|Residential and Commercial",
"Final Energy|Transportation",
"Final Energy|Bunkers",
NULL
)
fe_subtypes <- tribble(
~variable, ~label, ~color,
"Other", "Other" , "#ccc",
"Electricity", "Electricity", "#fc6",
"Hydrogen", "Hydrogen", "#aff",
"Heat", "Heat", "#e88",
"Solids|Biomass", "Solid Biomass", "#6b6",
"Gases", "All gases", "#774",
"Liquids", "All liquids", "#630",
"Solids|Coal", "Coal", "#111",
# "Solids|Coal", "Coal Solids", "#191919",
# "Solids|Biomass", "Biomass Solids", "olivedrab",
# "Liquids|Fossil", "Fossil Liquids", "gray40",
# "Liquids|Efuel", "Efuel Liquids", "mediumpurple4",
# "Gases|Efuel", "Efuel Gases", "plum2",
# "Gases|Biomass", "Biomass Gases", "green",
# "Gases|Fossil", "Fossil Gases", "gray90",
# "Liquids|Biomass", "Biomass Liquids", "olivedrab3",
)
fe.sec.labels <- setNames(fe_subtypes$label, fe_subtypes$variable)
fe.sec.vars <- names(fe.sec.labels)
plot.vars.color <- setNames(fe_subtypes$color, fe_subtypes$label)
for (v in vars) {
l <- fe.sec.labels
names(l) <- paste0(v, "|", names(l))
plotArea(
submissions = df.submissions,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = paste0(v, "|", fe.sec.vars),
plot.var.labels = l,
plot.colors = plot.vars.color,
y_label = paste0(v, "\n(EJ/yr)"),
total = v,
interpolate = T,
total.size = 1.1
) %>% print()
plotStackedBarModScen(
submissions = df.submissions,
plot.scen = scen.energyBarPlots,
plot.region = "World",
plot.vars = paste0(v, "|", fe.sec.vars),
plot.var.labels = l,
plot.colors = plot.vars.color,
plot.period = c(year.energyBarPlots),
y_label = paste0(v," in ",year.energyBarPlots,"\n(EJ/yr)"),
total = v,
bar.alpha = 0.8,
layout.axis.x.angle = 30
) %>% print()
}
## The following `from` values were not present in `x`: Final Energy|Other
## The following `from` values were not present in `x`: Final Energy|Other
## The following `from` values were not present in `x`: Final Energy|Transportation|Heat
## The following `from` values were not present in `x`: Final Energy|Transportation|Heat
## The following `from` values were not present in `x`: Final Energy|Bunkers|Heat, Final Energy|Bunkers|Solids|Biomass, Final Energy|Bunkers|Solids|Coal
## Warning: Removed 20 rows containing non-finite outside the scale range (`stat_align()`).
## The following `from` values were not present in `x`: Final Energy|Bunkers|Heat, Final Energy|Bunkers|Solids|Biomass, Final Energy|Bunkers|Solids|Coal
FE carrier per sector
total <- "Final Energy"
if(T) { # with grouped Transportation (w/ bunkers)
fe_data <- tribble(
~variable, ~label, ~color,
"Final Energy|Agriculture", "Agriculture", "#5b5",
"Final Energy|Industry|Other", "Industry Other", "#666",
"Final Energy|Residential and Commercial|Other", "R&C Other", "#888",
"Final Energy|Transportation (w/ bunkers)|Other", "Transportation Other","#444",
"Final Energy|Industry|Electricity", "Industry Elec", "#db5",
"Final Energy|Residential and Commercial|Electricity", "R&C Elec", "#fc6",
"Final Energy|Transportation (w/ bunkers)|Electricity", "Transport Elec", "#b85",
"Final Energy|Industry|Heat", "Industry Heat", "#e88",
"Final Energy|Residential and Commercial|Heat", "R&C Heat", "#faa",
"Final Energy|Industry|Hydrogen", "Industry H2", "#8dd",
"Final Energy|Residential and Commercial|Hydrogen", "R&C H2", "#aff",
"Final Energy|Transportation (w/ bunkers)|Hydrogen", "Transport H2", "#6bb",
"Final Energy|Industry|Solids", "Industry Solids", "#522",
"Final Energy|Residential and Commercial|Solids", "R&C Solids", "#855",
"Final Energy|Industry|Liquids", "Industry Liquids", "#99d",
"Final Energy|Residential and Commercial|Liquids", "R&C Liquids", "#66a",
"Final Energy|Transportation (w/ bunkers)|Liquids", "Transport Liquids", "#88b",
"Final Energy|Industry|Gases", "Industry Gases", "#a6a",
"Final Energy|Residential and Commercial|Gases", "R&C Gases", "#d9d",
"Final Energy|Transportation (w/ bunkers)|Gases", "Transport Gases", "#b8b",
"Final Energy|Non-Energy Use", "Non-energy", "#111",
"Final Energy|Other Sector", "Other", "#ccc",
)
} else { # with separated Transportation and Bunkers
fe_data <- tribble(
~variable, ~label, ~color,
"Final Energy|Other Sector", "Other", "#ccc",
"Final Energy|Agriculture", "Agriculture", "#5b5",
"Final Energy|Industry|Other", "Industry Other", "#666",
"Final Energy|Residential and Commercial|Other", "R&C Other", "#888",
"Final Energy|Transportation|Other", "Transport Other", "#444",
"Final Energy|Bunkers|Other", "Bunkers Other", "#333",
"Final Energy|Industry|Electricity", "Industry Elec", "#db5",
"Final Energy|Residential and Commercial|Electricity", "R&C Elec", "#fc6",
"Final Energy|Transportation|Electricity", "Transport Elec", "#b85",
"Final Energy|Bunkers|Electricity", "Bunkers Elec", "#974",
"Final Energy|Industry|Heat", "Industry Heat", "#e88",
"Final Energy|Residential and Commercial|Heat", "R&C Heat", "#faa",
"Final Energy|Industry|Hydrogen", "Industry H2", "#8dd",
"Final Energy|Residential and Commercial|Hydrogen", "R&C H2", "#aff",
"Final Energy|Transportation|Hydrogen", "Transport H2", "#6bb",
"Final Energy|Bunkers|Hydrogen", "Bunkers H2", "#599",
"Final Energy|Industry|Solids", "Industry Solids", "#522",
"Final Energy|Residential and Commercial|Solids", "R&C Solids", "#855",
"Final Energy|Industry|Liquids", "Industry Liquids", "#99d",
"Final Energy|Residential and Commercial|Liquids", "R&C Liquids", "#ccf",
"Final Energy|Transportation|Liquids", "Transport Liquids", "#88b",
"Final Energy|Bunkers|Liquids", "Bunkers Liquids", "#669",
"Final Energy|Industry|Gases", "Industry Gases", "#a6a",
"Final Energy|Residential and Commercial|Gases", "R&C Gases", "#d9d",
"Final Energy|Transportation|Gases", "Transport Gases", "#b8b",
"Final Energy|Bunkers|Gases", "Bunkers Gases", "#979",
"Final Energy|Non-Energy Use", "Non-energy", "#111",
)
}
plot.var.labels <- setNames(fe_data$label, fe_data$variable)
plot.vars.color <- setNames(fe_data$color, fe_data$label)
plotArea(
submissions = df.submissions,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = names(plot.var.labels),
plot.var.labels = plot.var.labels,
plot.colors = plot.vars.color,
y_label = "Final Energy\n(EJ/yr)",
total = total,
interpolate = T,
total.size = 1.1
) %>% print()
## Warning: Removed 300 rows containing non-finite outside the scale range (`stat_align()`).
plotStackedBarModScen(
submissions = df.submissions,
plot.scen = scen.energyBarPlots,
plot.region = "World",
plot.vars = names(plot.var.labels),
plot.var.labels = plot.var.labels,
plot.colors = plot.vars.color,
plot.period = c(year.energyBarPlots),
y_label = paste0(total, " in ", year.energyBarPlots, "\n(EJ/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
) %>% print()
Emissions
Sectoral emissions
total <- "Emissions|CO2|Energy and Industrial Processes"
emi_data <- tribble(
~variable, ~label, ~color,
"Emissions|CO2|Energy|Demand|Other Sector", "Other demand","#ccc",
"Emissions|CO2|Energy|Demand|Industry", "Industry", "#f84",
"Emissions|CO2|Energy|Demand|Residential and Commercial and AFOFI", "Build+AFOFI", "#7c5",
#"Emissions|CO2|Energy|Demand|AFOFI", "AFOFI", "#5a5",
#"Emissions|CO2|Energy|Demand|Residential and Commercial", "Buildings", "#8f4",
"Emissions|CO2|Energy|Demand|Transportation", "Transport", "#48f",
"Emissions|CO2|Energy|Demand|Bunkers", "Bunkers", "#25b",
"Emissions|CO2|Energy|Supply", "Supply", "#ff6",
"Emissions|CO2|Industrial Processes", "Ind. Proc.", "#e20"
)
emi.labels <- setNames(emi_data$label, emi_data$variable)
emi.colors <- setNames(emi_data$color, emi_data$label)
plotArea(
submissions = df.submissions,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = emi_data$variable,
plot.var.labels = emi.labels,
plot.colors = emi.colors,
y_label = "Emissions\n(MtCO2/yr)",
total = total,
interpolate = T,
total.size = 1.1
)
plotStackedBarModScen(
submissions = df.submissions,
plot.scen = scen.energyBarPlots,
plot.vars = emi_data$variable,
plot.var.labels = emi.labels,
plot.colors = emi.colors,
plot.period = c(year.energyBarPlots),
y_label = paste0("Emissions|CO2 in ", year.energyBarPlots, "\n(MtCO2/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
)
Net emissions
total = "Emissions|CO2"
df.emissions.co2 <- df.submissions %>%
filter(unit == "Mt CO2/yr") %>%
calc_addVariable("`Emissions|CO2|Others`" =
"`Emissions|CO2|Other` +
`Emissions|CO2|Other Capture and Removal` +
`Emissions|CO2|Product Use` +
`Emissions|CO2|Waste`",
units = "Mt CO2/yr", only.new = F, completeMissing = TRUE) %>%
calc_addVariable("`Emissions|CO2|Sum`" =
"`Emissions|CO2|AFOLU` +
`Emissions|CO2|Energy|Supply` +
`Emissions|CO2|Energy|Demand` +
`Emissions|CO2|Industrial Processes` +
`Emissions|CO2|Others`", units = "Mt CO2/yr", only.new = F, completeMissing = TRUE)
emi_data <- tribble(
~variable, ~label, ~color,
"Emissions|CO2|AFOLU", "AFOLU", "#8b8",
"Emissions|CO2|Energy|Supply", "Supply", "#ff6",
"Emissions|CO2|Energy|Demand", "Demand", "#6cc",
"Emissions|CO2|Industrial Processes", "Industrial Processes", "#e20",
"Emissions|CO2|Others", "Others", "#ccc",
)
emi.labels <- setNames(emi_data$label, emi_data$variable)
emi.colors <- setNames(emi_data$color, emi_data$label)
for (scen in selectedLowScens) {
p <- plotAreaOneScenario(
submissions = df.emissions.co2,
plot.scen = scen,
plot.period = period.energyAreaPlots,
plot.vars = emi_data$variable,
plot.var.labels = emi.labels,
plot.colors = emi.colors,
y_label = "CO2 Emissions\n(Mt CO2/yr)",
total = total,
total.label = "Total (reported)",
sum = "Emissions|CO2|Sum",
sum.label = "Sum (computed)",
interpolate = T,
total.size = 1.1,
) + ggtitle(scen)
print(p)
}
plotStackedBarModScen(
submissions = df.emissions.co2,
plot.scen = selectedLowScens,
plot.region = "World",
plot.vars = names(emi.labels),
plot.var.labels = emi.labels,
plot.colors = emi.colors,
plot.period = c(year.energyBarPlots),
y_label = paste0("Emissions|CO2 in ", year.energyBarPlots, "\n(EJ/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
) %>% print()
Gross Removal = Net Emissions - Gross Emissions
df.gross.emissions.co2 <- df.emissions.co2 %>%
calc_addVariable("`Computed Removal|CO2|Energy|Supply`" =
"`Emissions|CO2|Energy|Supply` - `Gross Emissions|CO2|Energy|Supply`",
units = "Mt CO2/yr", only.new = F) %>%
calc_addVariable("`Computed Removal|CO2|Energy|Demand`" =
"`Emissions|CO2|Energy|Demand` - `Gross Emissions|CO2|Energy|Demand`",
units = "Mt CO2/yr", only.new = F) %>%
calc_addVariable("`Computed Removal|CO2|Industrial Processes`" =
"`Emissions|CO2|Industrial Processes` - `Gross Emissions|CO2|Industrial Processes`",
units = "Mt CO2/yr", only.new = F)
emi_data <- tribble(
~variable, ~label, ~color,
"Emissions|CO2|AFOLU", "AFOLU", "#8b8",
"Gross Emissions|CO2|Energy|Supply", "Supply(+)", "#ff6",
"Gross Emissions|CO2|Energy|Demand", "Demand(+)", "#6cc",
"Gross Emissions|CO2|Industrial Processes", "IP(+)", "#e20",
"Computed Removal|CO2|Energy|Supply", "Supply(-)", "#dd5",
"Computed Removal|CO2|Energy|Demand", "Demand(-)", "#4aa",
"Computed Removal|CO2|Industrial Processes", "IP(-)", "#c00",
"Emissions|CO2|Others", "Others", "#ccc",
)
emi.labels <- setNames(emi_data$label, emi_data$variable)
emi.colors <- setNames(emi_data$color, emi_data$label)
for (scen in selectedLowScens) {
p <- plotAreaOneScenario(
submissions = df.gross.emissions.co2,
plot.scen = scen,
plot.region = "World",
plot.models = c("AIM", "GCAM", "IMAGE", "REMIND-MAgPIE", "WITCH"),
plot.vars = emi_data$variable,
plot.period = seq(2020, 2100, 5),
plot.var.labels = emi.labels,
plot.colors = emi.colors,
y_label = "CO2 Emissions\n(Mt CO2/yr)",
total = "Emissions|CO2",
total.label = "Total (reported)",
sum = "Emissions|CO2|Sum",
sum.label = "Sum (computed)",
interpolate = T,
total.size = 1.1,
) + ggtitle(scen) + geom_hline(yintercept = 0, color = "black", linewidth = 0.3)
print(p)
}
Carbon storage
total <- "Carbon Capture|Geological Storage"
ccs_data <- tribble(
~variable, ~label, ~color,
"Carbon Capture|Geological Storage|Other Sources", "Other", "#ccc",
"Carbon Capture|Geological Storage|Direct Air Capture", "Atmospheric", "#aff",
"Carbon Capture|Geological Storage|Synthetic Fuels", "Synthetic", "#66a",
"Carbon Capture|Geological Storage|Biomass", "Biomass", "#6b6",
"Carbon Capture|Geological Storage|Fossil", "Fossil", "#522",
"Carbon Capture|Geological Storage|Industrial Processes", "Industrial", "#2ba",
)
plot.var.labels <- setNames(ccs_data$label, ccs_data$variable)
plot.vars.color <- setNames(ccs_data$color, ccs_data$label)
# take the absolute value of storage values
df.plot <- df.submissions %>%
filter(variable %in% c(ccs_data$variable, total)) %>%
group_by(model, scenario, variable, region, period, value) %>%
mutate(value = abs(value)) %>%
ungroup()
p <- plotArea(
submissions = df.plot,
plot.scen = scenarios.energyAreaPlots,
plot.period = period.energyAreaPlots,
plot.vars = ccs_data$variable,
plot.var.labels = plot.var.labels,
plot.colors = plot.vars.color,
y_label = "Geological storage\n(Mt CO2/yr)",
total = total,
interpolate = T,
total.size = 1.1
) %>%
print()
plotStackedBarModScen(
submissions = df.plot,
plot.scen = scen.energyBarPlots,
plot.vars = names(plot.var.labels),
plot.var.labels = plot.var.labels,
plot.colors = plot.vars.color,
plot.period = c(year.energyBarPlots),
y_label = paste0(total, " in ", year.energyBarPlots, "\n(Mt CO2/yr)"),
total = total,
bar.alpha = 0.8,
layout.axis.x.angle = 30
)
Per capita indicators
mlp_vars <- c(
"Final Energy",
"Final Energy|Industry",
"Final Energy|Residential and Commercial",
"Final Energy|Transportation",
"Final Energy|Other Sector",
"Production|Iron and Steel|Steel",
"Production|Chemicals|High-Value Chemicals",
"Production|Non-Metallic Minerals|Cement Clinker",
"Energy Service|Transportation|Passenger|Road",
"Energy Service|Residential|Floor Space",
"Energy Service|Residential and Commercial|Floor Space",
NULL
)
scen <- intersect(union(LowScens,M),union(SSP1,SSP2))
# compute GDP per capita
# for models missing GDP and Population, could use average of other models
df.plot <- df.submissions %>%
filter(scenario %in% scen) %>%
calc_addVariable(
data.frame(
variable = paste("`GDP pCap`", sep=""),
formula = paste("(`GDP|PPP` / `Population` * 1000)", sep=""),
unit = "$2010/yr/cap"
),
only.new = F
)
for (v in mlp_vars) {
v_pCap <- paste(v, "pCap")
v.unit <- unique(filter(df.plot, variable == v)$unit)
# compute variable per capita
df.loop <- df.plot %>%
filter(variable %in% c(v, "Population", "GDP pCap")) %>%
calc_addVariable(
data.frame(
variable = paste("`", v_pCap, "`", sep=""),
formula = paste("(`", v, "` / `Population` * 1000)", sep=""),
unit = paste0(v.unit, " / bn cap")
),
only.new = F
)
plotLinesMultipleScenarios(
plot.var = v_pCap,
plot.scen = scen,
plot.region = "World",
submissions = df.loop,
y.split = NULL
) %>% print()
plotLinesXaxis(
df = df.loop,
var.x = "GDP pCap",
var.y = v_pCap
) %>% print()
plotMarkedLinesRegional(
plot.var = v_pCap,
plot.scen = c("Very Low with Limited Overshoot", "Medium Emissions"), #names(plot.emi.scen.letter),,
plot.region = c(RegionsTen, "World"),
plot.period = period.linePlots,
submissions = df.loop,
line.colors = c(brewer.pal(11, "Paired"), "#000000"),
line.types = plot.emi.scen.linetype, #c(1:100),
#historical = df.historical,
separate.models = TRUE,
linestyle.column = "emi.scen",
linestyle.header = "Emission scenario"
) %>% print()
}
